You will get APIs that will communicate with Front-end and Mobile applications.
Project details
I will assist you in building APIs that will communicate with Front-end, Mobile applications and IOT devices. I have more than 3 years of experience in backend development. I used different frameworks like Django REST, Flask and FastAPI for the development.
You will get quality work at a reasonable price. Don't think much just place the order.
You will get quality work at a reasonable price. Don't think much just place the order.
Programming Languages
PythonCoding Expertise
Performance Optimization, Security, DesignWhat's included
| Service Tiers |
Starter
$5
|
Standard
$15
|
Advanced
$30
|
|---|---|---|---|
| Delivery Time | 1 day | 3 days | 5 days |
Number of Revisions | 2 | 3 | 4 |
Number of Pages | 1 | ||
Design Customization | - | ||
Content Upload | - | - | - |
Responsive Design | - | - | - |
Source Code |
Optional add-ons
You can add these on the next page.
Additional Revision
+$2
Design Customization
(+ 1 Day)
+$5
Docker build
(+ 1 Day)
+$5Frequently asked questions
About Tahir
Backend Engineer & AI Developer | Python - APIs - LLMOps - Docker
Islamabad, Pakistan - 8:59 am local time
I am a Senior Backend and AI Developer specializing in building robust, production-ready backend architectures and integrating advanced AI capabilities. I bridge the gap between AI engineering and core backend infrastructure, ensuring your applications are fast, secure, and production-grade.
Whether you need a high-performance REST/gRPC API, a custom computer vision model, a production-ready GenAI chatbot, or self-hosted LLM deployment on a VPS, I deliver clean, containerized code that scales.
🚀 Core Expertise & Services
1. Robust Backend & API Development
- High-Performance APIs: Designing and optimizing secure, scalable APIs using Python (FastAPI, Django REST Framework) and NestJS.
- Asynchronous Pipelines: Implementing message brokers (RabbitMQ, Celery, Kafka) to handle heavy background processing and real-time streaming data.
- Database Design: Structuring and scaling relational and non-relational databases (PostgreSQL, MySQL, MongoDB) alongside Vector DBs for AI context.
2. Applied AI & Custom Model Training
- Computer Vision: Data preparation, training, and fine-tuning deep learning models for Classification, Object Detection, and Semantic Segmentation.
- Intelligent Document Processing: Developing custom, high-accuracy OCR pipelines to extract structured data from complex, unstructured documents.
3. Generative AI, Chatbots & LLMOps
- Advanced Chatbots: Building contextual, production-grade GenAI chatbots and multi-agent workflows using frameworks like LangChain and LangGraph.
- Model Integration: Seamless implementation of leading commercial models including OpenAI, Gemini, and Claude.
- Self-Hosted LLM Deployment: Deploying open-source models via Ollama and vLLM directly onto private Virtual Private Servers (VPS) to guarantee data privacy and drastically cut API costs.
4. DevOps, Deployment & System Observability
- Docker Containerization: Packaging full-stack backend and heavy AI applications into optimized Docker containers for seamless environment reproduction and zero-downtime deployment.
- AI Performance Dashboards: Setting up comprehensive Grafana observability stacks (integrated with Prometheus and Loki) to monitor system health, inference latency, API operational costs, and AI model accuracy in real time.
🛠️ Technical Stack
- Backend: Python (FastAPI, Django), JavaScript/TypeScript (NestJS, Prisma)
- AI/ML: TensorFlow, Keras, OpenCV, PyTorch, OCR Pipelines
- GenAI & LLMs: LangChain, LangGraph, OpenAI, Gemini, Claude, Ollama, vLLM
- Vector Databases: pgvector, Chroma, Pinecone, Milvus
- DevOps & Infra: Docker, Traefik, Nginx, Linux/Ubuntu Server Management, VPS Deployment
If you want an engineer who writes clean, test-driven Python code, understands containerization deeply, and knows how to operationalize AI without breaking your budget, let's talk.
Steps for completing your project
After purchasing the project, send requirements so Tahir can start the project.
Delivery time starts when Tahir receives requirements from you.
Tahir works on your project following the steps below.
Revisions may occur after the delivery date.
In Progress
Working on the project has started.
Testing
Work is completed. Testing is in progress.